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Energies
Volume 18
Issue 17
10.3390/en18174649
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Variable Dimensional Bayesian Method for Identifying Depth Parameters of Substation Grounding Grid Based on Pulsed Eddy Current

by
Xiaofei Kang
1,
Zhiling Li
1,
Jie Hou
1,
Su Xu
1,
Yanjun Zhang
1,
Zhihao Zhou
1 and
Jingang Wang
2,*
1
Baotou Power Supply Branch of Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Baotou 014030, China
2
School of Electrical Engineering, Chongqing University, Chongqing 400044, China
*
Author to whom correspondence should be addressed.
Energies 2025, 18(17), 4649; https://doi.org/10.3390/en18174649 (registering DOI)
Submission received: 14 July 2025 / Revised: 20 August 2025 / Accepted: 28 August 2025 / Published: 1 September 2025
(This article belongs to the Special Issue Reliability of Power Electronics Devices and Converter Systems)
Versions Notes

Abstract

The substation grounding grid, as the primary path for fault current dissipation, is crucial for ensuring the safe operation of the power system and requires regular inspection. The pulsed eddy current method, known for its non-destructive and efficient features, is widely used in grounding grid detection. However, during the parameter identification process, it is prone to local minima or no solution. To address this issue, this paper first develops a pulsed eddy current forward response model for the substation grounding grid based on the magnetic dipole superposition principle, with accuracy validation. Then, a variable dimensional Bayesian parameter identification method is introduced, utilizing the Reversible-Jump Markov Chain Monte Carlo (RJMCMC) algorithm. By using nonlinear optimization results as the initial model and introducing a dual-factor control strategy to dynamically adjust the sampling step size, the model enhances coverage of high-probability regions, enabling effective estimation of grounding grid parameter uncertainties. Finally, the proposed method is validated by comparing the forward response model with field test results, showing that the error is within 10%, demonstrating both the accuracy and practical applicability of the proposed parameter identification method.
Keywords: substation grounding grid; pulsed eddy current; forward response model; variable dimensional Bayesian; parameter identification substation grounding grid; pulsed eddy current; forward response model; variable dimensional Bayesian; parameter identification

Share and Cite

MDPI and ACS Style

Kang, X.; Li, Z.; Hou, J.; Xu, S.; Zhang, Y.; Zhou, Z.; Wang, J. Variable Dimensional Bayesian Method for Identifying Depth Parameters of Substation Grounding Grid Based on Pulsed Eddy Current. Energies 2025, 18, 4649. https://doi.org/10.3390/en18174649

AMA Style

Kang X, Li Z, Hou J, Xu S, Zhang Y, Zhou Z, Wang J. Variable Dimensional Bayesian Method for Identifying Depth Parameters of Substation Grounding Grid Based on Pulsed Eddy Current. Energies. 2025; 18(17):4649. https://doi.org/10.3390/en18174649

Chicago/Turabian Style

Kang, Xiaofei, Zhiling Li, Jie Hou, Su Xu, Yanjun Zhang, Zhihao Zhou, and Jingang Wang. 2025. "Variable Dimensional Bayesian Method for Identifying Depth Parameters of Substation Grounding Grid Based on Pulsed Eddy Current" Energies 18, no. 17: 4649. https://doi.org/10.3390/en18174649

APA Style

Kang, X., Li, Z., Hou, J., Xu, S., Zhang, Y., Zhou, Z., & Wang, J. (2025). Variable Dimensional Bayesian Method for Identifying Depth Parameters of Substation Grounding Grid Based on Pulsed Eddy Current. Energies, 18(17), 4649. https://doi.org/10.3390/en18174649

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